Powered leg prosthesis and control methodologies for obtaining near normal gait

ABSTRACT

A powered leg prosthesis including a powered knee joint with a knee joint and a knee motor unit for delivering power to the knee joint, a powered ankle joint coupled to the knee joint including an ankle joint and an ankle motor unit to deliver power to the ankle joint, a prosthetic foot coupled to the ankle joint, a plurality of sensors for measuring a real-time input, and controller for controlling movement of the prosthesis based on the real-time input. In the powered leg prosthesis, at least one of the knee motor unit or the ankle motor unit includes at least one drive stage, where the drive stage includes a rotary element for generating torque and at least one looped element affixed around the rotary element and configured for transmitting the torque to another rotary element coupled to a joint to be actuated.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Non-Provisional patentapplication Ser. No. 13/537,530, filed Jun. 29, 2012, which is acontinuation-in-part of U.S. Pat. No. 8,652,218, issued on Feb. 18,2014, which claims priority to and the benefit of ProvisionalApplication No. 61/046,684, filed Apr. 21, 2008, and is related to U.S.Non-Provisional application Ser. No. 13/115,175, filed May 25, 2011, thecontents of which are all hereby incorporated herein by reference intheir entireties.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under grant no.R01EB005684-01 awarded by the National Institutes of Health. Thegovernment has certain rights in the invention.

FIELD OF THE INVENTION

The invention relates to a powered leg prosthesis and controlmethodologies for controlling the prosthesis.

BACKGROUND

Leg prostheses can provide an artificial ankle, and artificial knee, orboth an artificial ankle and an artificial knee. A transfemoralprosthesis is a prosthesis designed for above the knee amputees.Transfemoral prostheses are generally more complicated than transtibialprostheses, as they must include a knee joint.

Nearly all current commercial transfemoral comprising prostheses areenergetically passive devices. That is, the joints of the prostheseseither store or dissipate energy, but do not provide net power over agait cycle. The inability to deliver joint power impairs the ability ofthese prostheses to restore many locomotive functions, including walkingup stairs and up slopes. Moreover, there is a need for a leg prosthesisthat provides a more natural gait behavior.

SUMMARY

Embodiments of the invention concern powered leg prostheses. A poweredleg prosthesis in accordance with the various embodiments can include apowered knee joint including a knee joint and a knee motor unit fordelivering power to the knee joint, a powered ankle joint coupled to theknee joint including an ankle joint and an ankle motor unit to deliverpower to the ankle joint, a prosthetic foot coupled to the ankle joint,a plurality of sensors for measuring a real-time input, and controllerfor controlling movement of the prosthesis based on the real-time input.In the powered leg prosthesis, at least one of the knee motor unit orthe ankle motor unit includes at least one drive stage, where the drivestage includes a rotary element for generating torque and at least onelooped element affixed around the rotary element and configured fortransmitting the torque to another rotary element coupled to a joint tobe actuated.

In one configuration of the powered leg prosthesis, the rotary elementcan be a pulley and the looped element can be a belt. The belt can be,for example, any of a flat belt, a round belt, a V-belt, multi-groovebelt, a ribbed belt, or a toothed belt. In another configuration of thepowered leg prosthesis, the rotary element can be a drive gear. In thisconfiguration, the looped element can be a chain. The leg prosthesis canfurther include a plurality of drive stages. Further, the rotary elementof a first of the plurality of drive stages and a rotary element of asecond of the plurality of drive stages can be the same or different.

In the various configurations of the leg prosthesis, at least onetensioning mechanism for maintaining a tension in the at least onelooped element can be provided. The tensioning mechanism can be, forexample, one of an eccentric mount or a swing arm. Further, thetensioning mechanism can be adjustable. In some configurations, thetensioning mechanism can be spring-loaded.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a view of a powered knee and ankle prosthesis, according toan embodiment of the invention.

FIG. 1B is an exploded view of the powered knee and ankle prosthesisshown in FIG. 1A, according to an embodiment of the invention.

FIG. 2 is an exploded view of knee motor unit, according to anembodiment of the invention.

FIG. 3 is an exploded view of ankle motor unit, according to anembodiment of the invention.

FIG. 4 is an exploded view of knee joint, according to an embodiment ofthe invention.

FIG. 5 is an exploded view of ankle joint, according to an embodiment ofthe invention.

FIGS. 6A and B are views of a foot having toe and heel force sensingelements, according to an embodiment of the invention.

FIG. 7 shows the joint angle and torque convention used herein. Positivetorque is defined in the direction of increasing angle.

FIG. 8 shows the subdivision of normal walking into four internal phasesshowing the knee and ankle angles during the phases, according to anembodiment of the invention.

FIG. 9 shows a finite-state model of normal walking, according to anembodiment of the invention. Each box represents a different internalphase and the transition conditions between the internal phases arespecified.

FIG. 10 shows piecewise fitting of knee and ankle torques during normalspeed level walk scaled for a 75 kg adult to a non-linear spring-damperimpedance model.

FIG. 11 is a diagram for an active/passive decomposition based controlof the powered knee and ankle prosthesis, according to an embodiment ofthe invention.

FIG. 12 is a diagram for a general form of active-passive decompositioncontrol including intent recognition that provides supervisorymodulation, according to an embodiment of the invention.

FIG. 13A is a side view of powered knee and ankle prosthesis, accordingto another embodiment of the invention.

FIG. 13B is a front view of powered knee and ankle prosthesis of FIG.13A.

FIGS. 14A and 14B show perspective and bottom views of an exemplarysagittal moment load cell suitable for use in the various embodiments ofthe invention.

FIG. 15 is a block diagram of an exemplary embedded microcontroller inaccordance with an embodiment of the invention.

FIG. 16 is a control state chart for the three activity modescorresponding to walking, standing, and sitting, and for the internalphases and their corresponding transitions within each activity mode.

FIG. 17 shows knee angle modulated knee stiffness during pre-stand(solid line) and pre-sit (dashed line) phases.

FIG. 18 is a plot of axial actuation unit force versus ankle angle.

FIG. 19 shows a normal speed walking phase portrait of the knee jointand four stride segments.

FIG. 20 shows the selection of indexing data samples during a firstsegment of a walking stride.

FIGS. 21A, 21B, and 21C are the output of the decomposition for Segment1 showing the spring and dashpot constants and the active and passiveknee torques.

FIG. 22 is a state chart for governing the discrete dynamics of anactive-passive decomposition controller in accordance with an embodimentof the invention.

FIG. 23 is a state chart for governing the discrete dynamics of thecadence estimator in accordance with an embodiment of the invention.

FIG. 24 is a schematic diagram of accelerometer measurements for slopeestimation in accordance with an embodiment of the invention.

FIG. 25 is a state chart for slope estimation in a controller inaccordance with an embodiment of the invention.

FIGS. 26A and 26B show front and back views of a friction/cable drivemotor in accordance with an embodiment of the invention.

FIG. 27 shows an exemplary embodiment of a belt drive transmission inaccordance with an embodiment of the invention.

FIGS. 28A and 28B show side views of first and second positions,respectively, achievable for an exemplary embodiment of a chain drivetransmission including an eccentric mount in accordance with anembodiment of the invention.

FIG. 29 illustrates schematically the components for the adjustablebearing mounts in FIGS. 28A and 28B.

FIG. 30 illustrates an exemplary configuration of a powered legprosthesis in accordance with the embodiments shown in FIGS. 27-29.

DETAILED DESCRIPTION

The invention is described with reference to the attached figures,wherein like reference numerals are used throughout the figures todesignate similar or equivalent elements. The figures are not drawn toscale and they are provided merely to illustrate the instant invention.Several aspects of the invention are described below with reference toexample applications for illustration. It should be understood thatnumerous specific details, relationships, and methods are set forth toprovide a full understanding of the invention. One having ordinary skillin the relevant art, however, will readily recognize that the inventioncan be practiced without one or more of the specific details or withother methods. In other instances, well-known structures or operationsare not shown in detail to avoid obscuring the invention. The inventionis not limited by the illustrated ordering of acts or events, as someacts may occur in different orders and/or concurrently with other actsor events. Furthermore, not all illustrated acts or events are requiredto implement a methodology in accordance with the invention.

The present inventors have observed that biomechanically normal walkingrequires positive power output at the knee joint and significant netpositive power output at the ankle joint. Embodiments of the inventionprovide a prosthesis that delivers power at both the knee and anklejoints. Unlike prior disclosed leg prosthetics that generate a desiredjoint trajectory for the prosthetic leg based on measurement of thesound leg trajectory and thus requires instrumentation of the sound leg,embodiments of the invention do not generally require instrumentation ofthe sound leg. Prostheses including transfemoral prostheses according toembodiments of the invention generally provide power generationcapabilities comparable to an actual limb and a gait-based controlframework for generating the required joint torques for locomotion whileensuring stable and coordinated interaction with the user and theenvironment. Embodiments of the invention thus enable the restoration ofsubstantially biomechanically normal locomotion.

One design for a prosthesis according to an embodiment of the inventionis shown in FIG. 1A through FIG. 6B. The prosthesis 100 comprises aprosthetic lower leg 101. Lower leg 101 can be coupled to a powered kneejoint comprising a knee motor unit 105 coupled to a knee joint 110, anda powered ankle joint comprising an ankle motor 115 coupled to an anklejoint 120. A sagittal plane moment sensor 125 can be located between theprosthesis and the user to measure the moment, and in one embodiment islocated immediately below the socket interface. In the embodiment shown,sensor 125 measures the sagittal plane moment, while separate sensorsdescribed below measure the ball of foot force and heel force withrespect to the ground or other object the foot is pressed against. Aload sensor 135 can be positioned at the ball of the foot, and a loadsensor 140 can be positioned at the heel of the foot. However, inanother embodiment (not shown) sensor 125 can measure the sagittal planemoment, the frontal plane moment and the axial force, such as providedby the three-axis socket load cell. This alternate embodiment caneliminate the need for sensor 135 and sensor 140.

Load sensors 141 and 142 are in series with each motor unit 105 and 115,respectively for motor unit force control. Position sensors 151 and 152are provided at each joint 110 and 120 as shown in FIGS. 4 and 5respectively. Position sensors 151 measure joint angle (0 as used below)and can be embodied as potentiometers. The computer/process controller,and power source (e.g. a battery such as a Li ion battery, andelectrical connections in the case of an electrical power source are notshown to avoid obscuring aspects of the invention. Non-electrical powersources may also be used, such as pneumatic power, or non-batteryelectrical sources, such as hydrogen-based fuel cells.

Prosthesis 100 is shown in an exploded view in FIG. 1B. Joints 110 and120 are more clearly shown as compared to FIG. 1A.

FIG. 2 is an exploded view of knee motor unit 105, according to anembodiment of the invention. Load sensor 141 is shown as a load cell(e.g. strain gauge). Load sensor 141 measures force and moments. Themotor unit 105 comprises a motor-driven ball screw assembly which drivesthe knee joint through a slider-crank linkage comprising screw 145.Other motor drive assemblies may also generally be used.

FIG. 3 is an exploded view of ankle motor unit 115, according to anembodiment of the invention. Load sensor 142 is generally analogous toload sensor 141. The motor unit 115 comprises a motor-driven ball screwassembly which drives the ankle joint through a slider-crank linkagecomprising screw 145. The ankle motor 115 includes a spring 147positioned to provide power in parallel (thus being additive) with powerprovided by the motor unit 115. Spring 147 biases the motor unit's forceoutput toward ankle plantarflexion, and supplements the power outputprovided by motor unit 115 during ankle push off.

FIG. 4 is an exploded view of knee joint 110, according to an embodimentof the invention. As described above, knee joint 110 includes positionsensor 151 that can be embodied as a potentiometer for anglemeasurements of the knee joint 110.

FIG. 5 is an exploded view of ankle joint 120, according to anembodiment of the invention. As described above, ankle joint 120includes position sensor 152 that can be embodied as a potentiometer forangle measurements of the ankle joint 120.

FIG. 6A is a view of a foot 170 having ball of foot sensors 135,according to an embodiment of the invention. Sensors 135 are provided tomeasure the ground reaction forces near the ball of the foot, such aswhen the foot strikes the ground. FIG. 6B is a view of a foot 170 havingball of foot sensors 135 and heel sensors 140, according to anembodiment of the invention. Sensors 140 are provided to measure theground reaction forces on the heel of the foot when the foot 170 strikesthe ground. Sensors 135 and 140 can be embodied as strain based sensors.

As described above, prostheses according to embodiments of the inventiongenerally provide a gait-based control framework for generating therequired joint torques for locomotion while ensuring stable andcoordinated interaction with the user and the environment. This enablesembodiments of the invention to restore substantially biomechanicallynormal locomotion.

Regarding control of the prosthesis, conventional prosthetic controlschemes utilize position-based control which comprises generation of adesired joint angle/position trajectories, which by its nature, mustutilize the prosthesis itself as a position source (e.g. “echo-control”based approaches). Such an approach poses several problems for thecontrol of a powered prosthesis, such as prostheses according toembodiments of the invention. First, the desired position trajectoriesare typically computed based on measurement of the sound side (normal)leg trajectory, which 1) is not well suited to bilateral amputees, 2)requires instrumentation of the sound side leg, and 3) generallyproduces an even number of steps, which can present a problem when theuser desires an odd number of steps. A subtle yet significant issue withconventional position-based control is that suitable motion trackingrequires a high output impedance (i.e., joints must be stiff), whichforces the amputee to react to the limb rather than interact with ormore generally control the prosthetic limb. Specifically, in order forthe known prosthesis to dictate the joint trajectory, it must generallyassume a high output impedance, thus substantially precluding dynamicinteraction with the user and the environment.

Unlike existing passive prostheses, the introduction of power into aprosthesis according to embodiments of the invention provides theability for the device to also act, rather than simply react. As such,the development of a suitable controller and control methodology thatprovides for stable and reliable interaction between the user andprosthesis is provided herein. Control according to embodiments of theinvention has been found to enable the user to interact with theprosthesis by leveraging its dynamics in a manner similar to normalgait, and also generates more stable and more predictable behavior.

Thus, rather than gather user intent from the joint angle measurementsfrom the contralateral unaffected leg, embodiments of the inventioninfer commands from the user via the (ipsilateral) forces and moments ofinteraction between the user and prosthesis. Specifically, the userinteracts with the prosthesis by imparting forces and moments from theresidual limb to the prosthesis, all of which can be measured viasuitable sensor(s), such as sensors 125, 140 and 141 described abovewhich measures moments/forces. These forces and moments serve not onlyas a means of physical interaction, but also serve as an implicitcommunication channel between the user and device, with the user'sintent encoded in the measurements. Inferring the user's intent from themeasured forces and moments of interaction according to embodiments ofthe invention provides several advantages relative to the known echoapproach.

In one embodiment of the invention the torque required at each jointduring a single stride (i.e. a single period of gait) can be piecewiserepresented by a series of passive impedance functions. A regressionanalysis of gait data indicates that joint torques can be characterizedby functions of joint angle (0) and angular velocity by an impedancemodel, such as the following exemplary passive impedance function shownin equation 1 below:

τ=k ₁(θ−θ_(e))+b*{dot over (θ)}  (1)

where k₁, b, and the equilibrium joint angle θ_(e) are all constantsthat are generally generated empirically, and are constants for a givenjoint during a given internal phase (e.g. knee, internal phase 3). k₁characterizes the linear stiffness. b is the linear damping coefficient,θ is the measured joint angle which can characterize the state of theprosthesis, θ_(e) is the equilibrium angle, {dot over (θ)} is theangular velocity of the joint, and τ is the joint torque. Given theseconstants, together with instantaneous sensor measurements for θ and{dot over (θ)}, the torque (τ) at the joints (knee and ankle) can bedetermined.

Positive directions of the angle (θ) and torque (τ) as used herein aredefined as shown in FIG. 7. If the coefficients b and k₁ are constrainedto be positive, then the joints will each exponentially converge to astable equilibrium at θ=θ_(e) and {dot over (θ)}=θ within each internalphase. That is, within any given internal phase, the actuators areenergetically passive (i.e. the joint will come to rest at a localequilibrium). While the unactuated prosthesis can be energeticallypassive, the behavior of one joint (knee or ankle) or the combinedbehavior of the knee and ankle joints, can be likewise passive, and thuswill generally respond in a predictable manner.

Responsive to direct input from the user (e.g. a heel strike) to triggera change in internal phase, power (torque) can be delivered from thepower source (e.g. battery) to the prosthesis in the proper magnitude toprovide the desired movement. Since the switching can be triggered bydirect input from the user related to the current internal phase, theuser maintains direct influence over the power applied to theprosthesis. If the user does not trigger the next internal phase (i.e.remains stationary) no net energy is delivered. That is, the prosthesiswill generally cease to receive power from the power source for movingthe joint, and will instead, due to the damped response, soon come torest at the local equilibrium identified with the present internalphase.

As described above, the decomposition of joint behavior into passivesegments requires the division of the gait cycle into a plurality ofinternal phases or “finite states” characterized by an impedancefunction and a set of constants for the impedance function, as dictatedby their functions and the character of the piecewise segments of theimpedance functions described above. The switching rules betweeninternal phases should generally be well defined and measurable, and thenumber of phases should be sufficient to provide a substantiallyaccurate representation of normal joint function. In one embodiment ofthe invention, the swing and stance phase of gait can constitute aminimal set of internal phases.

Based on least-squares regression fitting of Equation 1 to empiricalgait data, the present Inventors determined that such fits were improvedsignificantly by further dividing the two modes of swing and stance eachinto two additional internal phases to realize four phases, as shown inFIG. 8. A fifth internal phase can also be added, as illustrated in FIG.16. The angle (0) of the prosthetic knee (above) and ankle joint (below)can be provided during each internal phase as a function of the % of thestride. Angle values shown can be used as threshold values to triggerphase changes as described below relative to FIG. 9. As clear to onehaving ordinary skill in the art, the number of phases can be other thantwo or four.

FIG. 9 shows exemplary switching rules between internal phases forwalking. FIG. 16 shows another set exemplary switching rules, forwalking, standing, and sitting activity modes. As described above, ifthe user does not initiate actions that trigger the next phase (e.g.based on the switching rules), the prosthesis will cease to receivepower and will come to rest at the local equilibrium identified with thepresent phase. For example, switching can be based on the ankle angle>athreshold value (mode 1 to mode 2), or ankle torque<threshold) (mode 2to mode 3), the angle or torque measurements provided by on boardsensors as described above.

Phase 1 shown in FIG. 8 begins with a heel strike by the user (which canbe sensed by the heel force sensor), upon which the knee immediatelybegins to flex so as to provide impact absorption and begin loading,while the ankle simultaneously plantarflexes to reach a flat foot state.Both knee and ankle joints have relatively high stiffness (and can beaccounted for by k1 in equation 1) during this phase to prevent bucklingand allow for appropriate stance knee flexion, because phase 1 comprisesmost of the weight bearing functionality. Phase 2 is the push-off phaseand begins as the ankle dorsiflexes beyond a given angle (i.e. user'scenter of mass lies forward of stance foot). The knee stiffnessdecreases in this mode to allow knee flexion while the ankle provides aplantarflexive torque for push-off. Phase 3 begins as the foot leavesthe ground as detected by the ankle torque load cell and lasts until theknee reaches maximum flexion. Mode 4 is active during the extension ofthe knee joint (i.e. as the lower leg swings forward), which begins asthe knee velocity becomes negative and ends at heel strike (e.g. asdetermined by the heel force sensor).

In both of the swing phases (Phases 3 and 4), the ankle torque can besmall and can be represented in the controller as a (relatively) weakspring regulated to a neutral position. The knee can be primarilytreated as a damper in both swing phases.

Impedance modeling of joint torques was preliminarily validated byutilizing the gait data from a healthy 75 kg subject, as derived frombody-mass normalized data. Incorporating the four internal phasesdescribed above, along with the motion and torque data for each joint, aconstrained least-squares optimization was conducted to generate a setof parameters k₁, b and θ_(e) for each phase for each joint for use inEquation 1. The resulting parameter set can be fit to joint torques andis shown graphically in FIG. 10. FIG. 10 shows piecewise fitting of kneeand ankle torques during normal speed level walk scaled for a 75 kgadult to a non-linear spring-damper impedance model. The numbers shownin each phase represent the mean ratio of the stiffness forces todamping forces predicted by the fit. The vertical lines represent thesegmentation of a gait stride into four distinct phases. The fit shownin FIG. 10 clearly indicates that normal joint function can berepresented by the use of piecewise passive functions.

Controllers according to embodiments of the invention generally comprisean underlying gait controller (intra-modal controller). An optionalsupervisory gait controller (also called intent recognizer) can also beprovided. Both controllers generally utilize measured information. Thisinformation generally comprises user and ground interaction forces (F)and moments/torques (τ), joint angles and angular velocities fromon-board sensors, and can be used to extract real-time input from theuser. The gait control component utilizes the sensed instantaneousnature of the user input (i.e., moments and forces) to control thebehavior of the leg within a given activity mode, such as standing,walking, or stair climbing.

Two exemplary approaches to intra-modal impedance generation aredescribed below. The first approach is shown in FIG. 11 and represents ageneral form of active-passive decomposition-based intra-mode control.The second embodiment shown in FIG. 12 includes the control structureshown in FIG. 11 but adds a supervisory intent recognizing controller tomodulate the intra-modal control based on inputs from an intentrecognition module. As shown in FIGS. 11 and 12, F_(s) is the force theuser of the prosthesis is applying, such as a heel force in the case ofa heel strike, τ represents joint torque, and θ represent joint angles.τ_(a) represents the active component of joint torque which is roughlyproportional to the input force, and τ_(p) represents the passivecomponent of torque. The active joint torque τ_(a) is thus the totaljoint torque τ minus the passive joint torque, τp. Derivatives are shownusing the dot convention, with one dot being the first derivative (e.g.,{dot over (θ)} being angular velocity) and two dots representing thesecond derivative.

Intra-Modal Active-Passive Decomposition Control

In this embodiment of the intra-modal controller, shown in FIG. 11, thebehavior of the prosthesis can be decomposed into a passive componentand an active control component. The active control component is analgebraic function of the user's real-time input F_(s) (i.e., sensedsocket-prosthesis interface forces and moments and sensed groundreaction forces). The controller output is shown as the active torque(τ_(a)) minus the passive torque τ_(p). The controller outputτ_(a)−τ_(p) applied to the prosthetic leg based on dynamics of the legresponds via θ and {dot over (θ)}. The system response, θ and {dot over(θ)}, is fed back to the controller.

Power applied to the prosthesis can be thus commanded directly by theuser through measured interface forces and moments initiated by usermovements. In the absence of these commands from the user, F_(s)=0,τ_(a)=0 and the prosthesis fundamentally (by virtue of the controlstructure) cannot generate power, and thus only exhibits controlledpassive behavior. Due to the decomposition of energetic behaviorsinherent in this control structure, the prosthesis under it's owncontrol can be generally stable and passive. Unlike known echo controlapproaches, the input can be real-time, based only on the affected leg,and thus the approach can be equally applicable to bilateral andunilateral amputees and can reflect the instantaneous intent of theuser. Additionally, unlike echo control that is based on servocontrol,the prosthesis will exhibit a natural impedance to the user that shouldfeel more like a natural limb. These combined features should result inan active prosthesis that will feel inasmuch as possible like a naturalextension of the user. The structure and properties of both the gaitcontroller and intent recognizer are described below.

As described above, since gait is largely a periodic activity, jointbehavior can be functionally decomposed over a period by decomposing thejoint torque into a passive component and an active component. Thepassive component can comprise a function of angle (i.e., single-valuedand odd), and a function of angular velocity passive (i.e.,single-valued and odd), such as equation 1 described above. The activecomponent can be a function of the user input (i.e., socket interfaceforces). Given a set of data that characterizes a nominal period ofjoint behavior, the passive component can be first extracted from thewhole, since the passive behavior is a subset of the whole (i.e., thepassive component consists of single-valued and odd functions, while theactive has no restrictions in form). The passive component can beextracted by utilizing a least squares minimization to fit a generalizedsingled-valued odd function of angle and angular velocity to the torque.Once the passive component is extracted, the residual torque (i.e., theportion that is not extracted as a passive component), can beconstructed as an algebraic function of the sensed socket interface andground reaction forces (i.e., the direct-acting user input) byincorporating a similar candidate function, but not restricted to be ofpassive form. Finally, superimposing the passive and active componentsprovides a decomposed functional approximation of the original periodjoint torque.

Intra-Modal Locally Passive Event-Triggered Control

In this embodiment of the intra-modal controller shown in FIG. 12, asupervisory intent recognizer can be added that utilizes the same senseduser inputs (i.e., moments and forces) as the intra-modal/gaitcontroller, but extracts the user's intent based on the characteristicshape of the user input(s) and system response (e.g. F, θ, θ-dot). Basedon the extracted intent, the supervisory intent recognizer modulates thebehavior of the underlying gait controller to smoothly transitionbehavior within a gait (e.g., speed and slope accommodation) and betweengaits (e.g., level walk to stair ascent), thus offering a unifiedcontrol structure within and across all gaits.

Gait intent recognition can be a real time pattern recognition or signalclassification problem. The signal in this case is generally thecombination of socket interface forces Fs and the dynamic state of theprosthesis, which in one embodiment can be a vector of the knee andankle angles θ for a powered leg prosthesis according to an embodimentof the invention. A variety of methods exist for pattern recognition andsignal classification including nearest neighbor algorithms, neuralnetworks, fuzzy classifiers, linear discriminant analysis, and geneticalgorithms.

Sensors

As described above, embodiments of the invention include a number ofsensors for providing signals for adjusting operation of a leg and ankleprosthesis. A description of one exemplary arrangement of sensors can bedescribed below with respect to FIGS. 13A, 13B, 14A, and 14B. FIG. 13Ais a side view of powered knee and ankle prosthesis 1300, according toanother embodiment of the invention. FIG. 13B is a front view of poweredknee and ankle prosthesis of FIG. 13A. FIGS. 14A and 14B showperspective and bottom views of an exemplary sagittal moment load cellsuitable for use in the various embodiments of the invention.

Each joint actuation unit, such as knee actuation unit 1302 and ankleactuation unit 1304 in FIG. 13A, can include a uniaxial load cellpositioned in series with the actuation unit for closed loop forcecontrol. Both the knee and ankle joints can incorporate integratedpotentiometers for joint angle position. The ankle actuation unit caninclude a spring 1305, as described above with respect to FIGS. 1A-4.One 3-axis accelerometer can be located on the embedded system 1306 anda second one can located below the ankle joint 1308 on the ankle pivotmember 1310. A strain based sagittal plane moment sensor 1312, such assensor 1400 shown in FIGS. 14A and 14B, can located between the kneejoint 1314 and the socket connector 1316, which measures the momentbetween a socket and the prosthesis. In the various embodiments of theinvention, a sagittal plane moment sensor can be designed to have a lowprofile in order to accommodate longer residual limbs. The sensor canincorporate a full bridge of semiconductor strain gages which measurethe strains generated by the sagittal plane moment. In one embodiment ofthe invention, the sagittal plane moment sensor was calibrated for ameasurement range of 100 Nm. A custom foot 1318 can designed to measurethe ground reaction force components at the ball 1320 of the foot andheel 1322. The foot can include of heel and ball of foot beams, rigidlyattached to a central fixture and arranged as cantilever beams with anarch that allows for the load to be localized at the heel and ball ofthe foot, respectively. Each heel and ball of foot beam can alsoincorporates a full bridge of semiconductor strain gages that measurethe strains resulting from the respective ground contact forces. In oneembodiment of the invention, the heel and ball of foot load sensors werecalibrated for a measurement range of 1000 N. In addition, incorporatingthe ground reaction load cell into the structure of a custom foot caneliminate the added weight of a separate load cell, and also enablesseparate measurement of the heel and ball of foot load. The prostheticfoot can be designed to be housed in a soft prosthetic foot shell (notshown).

Microcontroller System

The powered prosthesis contains an embedded microcontroller that allowsfor either tethered or untethered operation. An exemplary embeddedmicrocontroller system 1500 is shown in the block diagram in FIG. 15.The embedded system 1500 consists of signal processing, power supply,power electronics, communications and computation modules. The systemcan be powered by a lithium polymer battery with 29.6 V. The signalelectronics require +/−12 V and +3.3 V, which are provided via linearregulators to maintain low noise levels. For efficiency, the batteryvoltage can be reduced by PWM switching amplifiers to +/−15 V and +5 Vprior to using the linear regulators. The power can be disconnected viaa microcontroller that controls a solid state relay. The power statuscan be indicated by LED status indicators controlled also by themicrocontroller.

The analog sensor signals acquired by the embedded system include theprosthesis sensors signals (five strain gage signals and twopotentiometer signals), analog reference signals from the laptopcomputer used for tethered operation, and signals measured on the boardincluding battery current and voltage, knee and ankle servo amplifiercurrents and two 3-axis accelerometers. The prosthesis sensor signalsare conditioned using input instrumentation amplifiers. The battery,knee motor and ankle motor currents are measured by current senseresistors and current sensing amplifiers. The signals are filtered witha first-order RC filter and buffered with high slew rate operationalamplifiers before the analog to digital conversion stage. Analog todigital conversion can be accomplished by two 8-channel analog todigital convertors. The analog to digital conversion data can betransferred to the microcontroller via serial peripheral interface (SPI)bus.

The main computational element of the embedded system can be a 32-bitmicrocontroller. In the untethered operation state, the microcontrollerperforms the servo and activity controllers of the prosthesis and datalogging at each sample time. In addition to untethered operation, theprosthesis can also be controlled via a tether by a laptop computerrunning MATLAB Simulink RealTime Workshop. In the tethered operationstate, the microcontroller drives the servo amplifiers based on analogreference signals from the laptop computer. A memory card can be usedfor logging time-stamped data acquired from the sensors and recordinginternal controller information. The memory chip can be interfaced tothe computer via wireless USB protocol. The microcontroller sends PWMreference signals to two four quadrant brushless DC motor drivers withregenerative capabilities in the second and forth quadrants of thevelocity/torque curve.

Control of Sitting and Standing

In some embodiments of the invention, additional controls can beprovided for operating the prosthesis when going from a sitting to astanding position or vice versa. This can be implemented via the use ofa sitting mode controller implemented in the microcontroller. Operationof the sitting mode controller consists of four phases that are outlinedin the general control state chart shown in FIG. 16. As shown in FIG.16, two phases are primary sitting phases, weight bearing and non-weightbearing. The other two phases encompass the transition phases, pre-standand pre-sit, for standing up and sitting down, respectively. Weightbearing and non-weight bearing are the primary sitting phases thatswitch the knee and ankle joints between high and low impedances,respectively. The transition phases, pre-stand and pre-sit, modulate thestiffness of the knee as a function of knee angle, as shown in FIG. 17,to assist the user in standing up and sitting down. FIG. 17 shows kneeangle modulated knee stiffness during pre-stand (solid line) and pre-sit(dashed line) phases.

The modulation allows for smoother transitions near the seated position.The ankle joint can be slightly dorsiflexed with moderate stiffnessduring the standing up and sitting down phases. Switching between thefour sitting phases occurs when sensor thresholds are exceeded, asdepicted FIG. 16. The parameters of the impedance based controllers aretuned using a combination of feedback from the user and joint angle,torque and power data from the prosthesis.

Mechanical Design

In the various embodiments of the invention, actuation for theprosthesis can be provided by two motor-driven ball screw assembliesthat drive the knee and ankle joints, respectively, through aslider-crank linkage. The prosthesis can be capable of 120° of flexionat the knee and 45° of planterflexion and 20° of dorsiflexion at theankle. In one embodiment, each actuation unit consists of a DC motor(such as a Maxon EC30 Powermax) connected to a 12 mm diameter ball screwwith 2 mm pitch, via helical shaft couplings. An exemplary ankleactuation unit additionally incorporates a 302 stainless steel spring(51 mm free length and 35 mm outer diameter), with 3 active coils and astiffness of 385 N/cm in parallel with the ball screw.

As described above with respect to FIGS. 1A-4, the purpose of the springcan be to bias the motor's axial force output toward ankleplantarflexion, and to supplement power output during ankle push off.The stiffness of the spring can be maximized to allow for peak forceoutput without limiting the range of motion at the ankle. The resultingaxial actuation unit's force versus ankle angle plot can be shown inFIG. 18. FIG. 18 is a plot if axial force as a function of ankle angleillustrating spring force, actuator force and total force. FIG. 18graphically demonstrates for fast walking the reduction in linear forceoutput supplied by the motor at the ankle through the addition of thespring. Note that the compression spring does not engage untilapproximately five degrees of ankle plantarflexion. Each actuation unitcan include a uniaxial load cell (such as Measurement SpecialtiesELPF-500L), positioned in series with the actuation unit for closed loopforce control of the motor/ballscrew unit. Both the knee and anklejoints can incorporate bronze bearings and, for joint angle measurement,integrated precision potentiometers (such as an ALPS RDC503013). Astrain based sagittal plane moment sensor, as previously described withrespect to FIGS. 14A and 14B can be located between the knee joint andthe socket connector, which measures the moment between the socket andprosthesis. The ankle joint connects to a foot, which incorporatesstrain gages to measure the ground reaction forces on the ball of thefoot and on the heel. The central hollow structure houses alithium-polymer battery and provides an attachment point for theembedded system hardware. To better fit with an anthropomorphicenvelope, the ankle joint can be placed slightly anterior to thecenterline of the central structure. This gives the prosthesis theillusion of flexion when the amputee can be standing vertically with theknee fully extended.

The length of the shank segment can be varied by changing the length ofthree components; the lower shank extension, the spring pull-down, andthe coupler between the ball nut and ankle. Additional adjustability canbe provided by the pyramid connector that can be integrated into thesagittal moment load cell for coupling the prosthesis to the socket (asis standard in commercial transfemoral prostheses). In one embodiment ofthe invention, the self-contained transfemoral prosthesis was fabricatedfrom 7075 aluminum and has a total mass of 4.2 kg, which can be withinan acceptable range for transfemoral prostheses, and comparable to anormal limb segment. A weight breakdown of an exemplary device ispresented below in Table I.

TABLE II MASS BREAKDOWN OF SELF-CONTAINED POWERED PROSTHESIS. ComponentMass (kg) Battery 0.62 Electronics 0.36 Knee Motor Assembly 0.72 AnkleMotor Assembly 0.89 Sensorized Foot 0.35 Foot Shell 0.24 Sagittal MomentSensor 0.12 Remaining Structure 0.90 Total Weight 4.20

Active Passive Torque Decomposition

Passive joint torque, τ_(p), can be defined as the part of the jointtorque, τ, which can be represented using spring and dashpotconstitutional relationships (passive impedance behavior). The systemcan only store or dissipate energy due to this component. The activepart can be interpreted as the part which supplies energy to the systemand the active joint torque can be defined as τ_(a)=τ−τ_(p). This activepart can be represented as an algebraic function of the user input viathe mechanical sensory interface (i.e socket interface forces andtorques).

Gait is considered a mainly periodic phenomena with the periodscorresponding to the strides. Hence, the decomposition of a stride willgive the required active and passive torque mappings for a specificactivity mode. In general, the joint behavior exhibits varying activeand passive behavior in each stride. Therefore, segmenting of the stridein several parts can be necessary. In this case, decomposition of thetorque over the entire stride period requires the decomposition of thedifferent segments and piecewise reconstruction of the entire segmentperiod. In order to maintain passive behavior, however, the segmentscannot be divided arbitrarily, but rather can only be segmented when thestored energy in the passive elastic element is zero. This requires thatthe phase space can only be segmented when the joint angle begins andends at the same value. FIG. 19 shows the phase portrait of normal speedwalking and the four different stride segments, S₁, S₂, S₃ and S₄. Thus,the entire decomposition process consists of first appropriatesegmentation of the joint behavior, followed by the decomposition ofeach segment into its fundamental passive and active components.

The decomposition of each segment shown in FIG. 19 can be converted toan optimization problem. In each segment of the stride, 2n data pointsare selected by sampling the angular position in equal intervals betweenits minimum and maximum and selecting the corresponding positive andnegative angular velocities. In this work, the number of angularposition samples for each segment, n can be set to be 100. Theconstrained least squares optimization problem given in Equation 2 belowcan be constructed and solved.

$\begin{matrix}{{\min\limits_{x}{\frac{1}{2}{{{Cx} - d}}_{2}^{2}\mspace{14mu} {s.t.\mspace{14mu} 0}}} \leq x} & (2)\end{matrix}$

where C, x and d are defined in Equations 3, 4, and 5 below,respectively. The indexing of the joint angular position, angularvelocity and moment samples are explained via the sketch in FIG. 20.FIG. 20 shows a selection and indexing of data samples from a firstsegment.

$\begin{matrix}{C_{4{nx}\; 3\; n} = \left\lbrack {C_{1}\mspace{14mu} C_{2}\mspace{14mu} C_{3}} \right\rbrack^{T}} & (3) \\{{{{C_{1} = \left\lbrack {\begin{matrix}{{diag}\left( {\begin{bmatrix}\theta_{1} \\\theta_{2} \\\vdots \\\theta_{n}\end{bmatrix}_{{nx}\; 1} - \alpha} \right)} \\{{diag}\left( {\begin{bmatrix}\theta_{1} \\\theta_{n - 1} \\\vdots \\\theta_{1}\end{bmatrix}_{{nx}\; 1} - \alpha} \right)}\end{matrix}{{diag}\left( \begin{bmatrix}{\overset{.}{\theta}}_{1} \\{\overset{.}{\theta}}_{2} \\\vdots \\\vdots \\\vdots \\{\overset{.}{\theta}}_{n}\end{bmatrix}_{2{nx}\; 1} \right)}} \right\rbrack_{2{nx}\; 3n}}C_{2}} = \left\lbrack {\begin{matrix}C_{21} \\C_{22}\end{matrix}\mspace{14mu} C_{23}} \right\rbrack_{{2n} - {1x\; 3n}}}{C_{21} = \begin{bmatrix}\theta_{1} & {- \theta_{2}} & 0 & \ldots & 0 \\0 & \ddots & \ddots & \ddots & \vdots \\\vdots & \ddots & \theta_{n - 1} & \theta_{n} & 0 \\0 & \ldots & 0 & 0 & 0\end{bmatrix}_{nxn}}{C_{22} = \begin{bmatrix}\theta_{n} & {- \theta_{n - 1}} & 0 & \ldots & 0 \\0 & \ddots & \ddots & \ddots & \vdots \\\vdots & \ddots & \theta_{3} & {- \theta_{2}} & 0 \\0 & \ldots & 0 & \theta_{2} & {- \theta_{1}}\end{bmatrix}_{n - {1{xn}}}}{C_{23} = \begin{bmatrix}{\overset{.}{\theta}}_{1} & {- {\overset{.}{\theta}}_{2}} & 0 & \ldots & 0 \\0 & \ddots & \ddots & \ddots & \vdots \\\vdots & \ddots & {\overset{.}{\theta}}_{{2n} - 2} & {- {\overset{.}{\theta}}_{{2n} - 1}} & 0 \\0 & \ldots & 0 & {\overset{.}{\theta}}_{{2n} - 1} & {- {\overset{.}{\theta}}_{2n}}\end{bmatrix}_{{2n} - {1{x2n}}}}{C_{3} = \left\lbrack {\beta \mspace{14mu} \beta \mspace{14mu} \ldots \mspace{14mu} \ldots \mspace{14mu} \ldots \mspace{14mu} \beta \mspace{14mu} \beta} \right\rbrack_{1x\; 3n}}} & \; \\{x_{3{nx}\; 1} = \begin{bmatrix}k_{1} \\k_{2} \\\vdots \\k_{n - 1} \\k_{n} \\b_{1} \\b_{2} \\\vdots \\b_{{2n} - 1} \\b_{2n}\end{bmatrix}} & (4)\end{matrix}$

The matrix C consists of three sub-matrices, C₁, C₂ and C₃. C₁ can bethe main part responsible for the fitting of the spring and dashpotconstants, k and b. C₂ bounds the rate of change of the passive jointtorque and ensures smoothness in the resulting passive joint torque, andC₃ is basically a row of penalty constants, β, which penalizes largevalues of the spring and dashpot constants and thus limits themagnitudes of both. In this work, β is set to 0.1.

The origin of each virtual spring can be also added to the optimizationproblem formulation as a parameter in order to obtain a tighter passivetorque fit. Therefore, the optimization problem given by (3) can besolved iteratively for a range of values of spring origin constant, α.The solution with the least error norm can be selected as the optimalsolution.

The result of the above stated constrained optimization problem forsegment 1 can be shown in plots in FIGS. 21A-C. FIGS. 21A-C are theoutput of the decomposition for s₁ in FIG. 19 showing the spring anddashpot constants and the active and passive knee torques (Springorigin, α is 23 degrees).

As can be seen from FIGS. 21A-C, the decomposed passive part can be verysimilar to the joint torque, and thus it can be stated that the behaviorof the joint can be mainly passive. The result of the decomposition forthe segment S can be stored in R_(i) of the form given in Equation 6.

R _(i)=[θ{dot over (θ)}τ_(pas) F _(S1) F _(S2)τ_(act)]_(2n×6)  (6)

where τ_(pas)=C₁x.

The procedure presented above decomposes the joint torques into activeand passive parts. The joint torque references for the control of theprosthesis are generated by combining this active and passive torques.There are two major challenges to be solved. Firstly, the correct motionsegment must be selected. Secondly, after the motion segment is selectedat each sampling instant a new joint torque reference can be generatedusing the discrete mappings for the active and passive torque parts.

A switching system modeling approach incorporating both discrete andcontinuous states can be used for the reconstruction of the torquereference signal. The state chart shown in FIG. 22. will govern thediscrete dynamics of the controller. Since the sequence of the segmentscan be ordered (i.e., the direction of the motion for a specific gaitphase does not change), each segment can transition only to the nextone, where the transition guard function can be written as a inequalityin terms of θ and {dot over (θ)}. The transitions between segments takeno time and the dynamics of the controller are governed by the {f_(p)_(i) (θ,{dot over (θ)}); f_(a) _(i) (F_(S))} pair at each samplinginstant. The joint reference torque is

τ_(ref)=τ_(a)+τ_(p) =f _(p) _(i) (θ,{dot over (θ)})±f _(a) _(i) (F_(S))  (7)

The decomposition algorithm presented above gives the result matrix, R,for each segment. The discrete data in R can be used to construct thejoint torque reference for the continuous measurements of another trialin the same gait phase. At each sampling instant of the algorithm, themeasurement vector m=[θ_(m),{dot over (θ)}_(m),F_(S1) _(_) _(m),F_(S2)_(_) _(m)]^(T) can be acquired. For the reconstruction of the passiveknee torque part, the Euclidian error norm between the [θ_(m) {dot over(θ)}_(m)]^(T) and the angular position and velocities of all the samplesin that segment [θ_(i) {dot over (θ)}_(i)]^(T) can be calculated asshown in Equation 8 and stored in the vector e.

e _(i)=√{square root over ((θ_(m)−θ_(i))²+({dot over (θ)}_(m)−{dot over(θ)}_(i))²)}  (8)

Then two elements of this vector with the least error norm are found andthe passive knee torque reference can be found as a weighted linearcombination of the passive knee torques corresponding to these points.The reconstruction of the active knee torque part is similar where only{θ,{dot over (θ)},τ_(pas)} is exchanged with {F_(S1),F_(S2),τ_(act)}.

Intent Recognition

The supervisory controller (intent recognizer) switches among differentunderlying intramodal controllers depending on the activity mode theuser imposes on the prosthesis. The intent recognizer consists of threeparts: activity mode recognizer, cadence estimator and the slopeestimator.

The activity mode recognizer detects the activity mode of the prosthesis(standing, walking, sitting, stair ascent or stair descent, etc. . . .). This can be accomplished by comparing the features which aregenerated in real time to a feature database using some machine learningand/or pattern recognition methods. The present implementation of thegait mode recognizer, which recognizes standing and walking modes, isdescribed below.

Firstly, a database which contains all the possible activity modes(standing and walking in this case) can be generated by makingexperimental trials. In the experimental trials, the user can be askedto walk or stand in different controller modes for 50 second longtrials. The socket sagittal moment above the knee joint, foot heel load,foot ball load, knee angle, knee velocity, ankle angle and anklevelocity are recorded with 1 ms sampling period. It should be noted thatother sensor signals such as accelerations and electromyographymeasurements from the residual limb can be added to the list of thesignals used for intent recognition. For example, from the recordedexperimental trials, 10000 random frames (5000 standing and 5000walking) of 100 samples length are generated for all the seven recordedsignals. The mean and the standard deviation of each frame are computed.The mean and standard deviation of signals are selected as the featuressince minimal computation can be required to obtain them. A databasecontaining 10000 samples with 14 features (mean and standard deviationof the seven signals) belonging to two classes (standing and walking)can be generated. After the database is generated, the dimension of thedatabase can be reduced from 14 to three using principal componentanalysis (PCA). Dimension reduction can be necessary because patternrecognition for high dimensional datasets can be computationallyintensive for real-time applications. After dimension reduction step,the standing and walking data can be modeled with Gaussian mixturemodels. Gaussian mixture models represent a probability distribution asa sum of several normal Gaussian distributions. The order of theGaussian mixture model for each mode can be determined according to theMinimum Description Length Criteria.

As described above, the database generation, dimension reduction and theGaussian mixture modeling are explained. For real-time decision making,overlapping frames of 100 samples can be generated at each 10 msinterval. 14 features described above are extracted from these framesand the PCA dimension reduction can be applied to these features to geta reduced three dimensional feature vector. The reduced dimensionfeatures can be fed to the Gaussian mixture models for standing andwalking and the probability of the sample vector being standing orwalking can be computed. The mode with the greater probability isselected as the instantaneous activity mode. Since one decision mightgive wrong results in some cases due to noise, disturbance, etc. . . . ,a voting scheme can be used to enhance the results. In the votingscheme, the controller activity mode is switched if and only if morethan 90 percent of the instantaneous activity mode decisions among thelast 40 decisions are a specific activity mode. Once a new activity modeis selected by the voting scheme, the underlying activity controller canbe switched to the corresponding mode.

Such an activity mode recognizer is provided by way of illustration andnot as a limitation. In the various embodiments of the invention, one ormore parts of the algorithm might be modified. For example, in someembodiments, different features such as mean, max, kurtosis, median, ARcoefficients, wavelet based features, frequency spectrum based featuresof the frame might be generated. Additionally, different dimensionreduction techniques such as linear discriminant analysis, independentcomponent analysis might be employed. Furthermore, differentclassification methods such as artificial neural networks, supportvector machines, decision trees, hidden Markov models might be used.

Cadence and Slope Estimation

Cadence estimation is accomplished by observing peak amplitudes incharacteristic signal data and then measuring the time betweensuccessive peaks. Since walking is a cyclic activity each of the sensorsignals will be periodic of cadence. The most relevant sensor signalswill contain only one characteristic amplitude peak per stride such asfoot heel load and the ball of foot load. In the real-timeimplementations, cadence estimation is accomplished by recording thefoot load after heel strike when it exceeds 400 N until the loaddecreases below 350 N. Then, the time of occurrence of the peak load inthis window is found and the previous peak time is subtracted from thenew peak time. This corresponds to stride time and can be converted tocadence (steps/min) by multiplying with 120. Once the cadence isestimated, the intent recognizer selects the corresponding middle layercontroller based on some predefined thresholds as in FIG. 23.

For example, in some embodiments, a 3D accelerometer capable ofmeasuring ±3 g accelerations is embedded into the ankle joint couplerwhere the prosthetic foot is connected. An exemplary arrangement of sucha system is shown by the schematic in FIG. 24. The accelerometermeasurements are used to estimate the ground slope. In order to estimatethe ground slope, the accelerometer data in tangential direction isused. Assuming the foot is flat on the ground, the ground slope angle,θ_(s), can be calculated as in equation (9) below.

$\begin{matrix}{\theta_{s} = {\sin^{- 1}\left( \frac{a_{t}}{g} \right)}} & (9)\end{matrix}$

In Eqn. 9, g is the gravitational constant. In order to find the groundslope estimate, {circumflex over (θ)}_(s), the accelerometer data shouldbe collected while the foot is flat on the ground as determined by theheel and ball of the foot load sensors. While the foot is flat on theground, equation (1) is computed for the frame of the collected data andthe mean of this frame is outputted as the ground slope estimate,{circumflex over (θ)}_(s). Once the slope is estimated, the intentrecognizer selects the corresponding middle layer controller based onsome predefined thresholds. An exemplary state chart for such an intentrecognizer is shown in FIG. 25.

Friction and Cable Drive Based Actuation

Rather than a ballscrew and slider crank embodiment for the transmissionof torque from a motor to the ankle and/or knee units, in someembodiments of the invention, the prosthesis can incorporate a frictionand cable drive transmission embodiment. FIGS. 26A and 26B show frontand back views of an exemplary embodiment of a friction drivetransmission 2600 in accordance with an embodiment of the invention. Asshown in FIGS. 26A and 26B, the shaft 2602 of an electric motor 2604 ispreloaded against a first stage in a housing 2606, such as a largerdiameter cylinder or friction drive gear 2608, which creates sufficientfriction to transmit torque without slip. The shaft 2602 can use one ormore friction rollers 2610 to transmit the torque. The first stage ofthe friction drive can also be supplemented with a second stage. Thefriction drive gear 2608 drives a smooth pinion 2612 directly, which ispreloaded against a larger diameter cylinder or cable gear output 2614in the housing 2606, which in turn transmits torque directly to the kneeor ankle joint.

In addition to, or rather than a friction drive, the first or secondstage of the transmission can alternatively be embodied by a cable drivetransmission, in which a cable is wrapped around the circumference of alarger diameter cylinder, such as friction drive gear 2608, and alsoaround the circumference of a smaller diameter cylinder, such as pinion2612. In such embodiments, the cable is affixed to the friction drivegear 2608, and is pretensioned, using a tensioning screw 2616 or similarmeans, around both the drive gear 2608 and pinion 2612, such thatfriction between cable and pinion 2612 enables the transmission oftorque from between the pinion 2612 and drive gear 2608. In oneembodiment of a combined friction drive/cable drive transmission can beused, in which a first stage of the transmission (i.e., the frictiondrive gear 2608 connected directly to the electric motor 2604) is of thefriction drive type, while the second stage of the transmission (i.e.,the cable gear output 2614 connected directly to the knee or anklejoint) is of the cable drive type.

Chain Drive or Belt Drive Based Actuation

Rather than the ballscrew and slider crank or the friction drive andcable drive embodiments for the transmission of torque from a motor tothe ankle and/or knee units, in some embodiments of the invention, theprosthesis can incorporate a chain drive or a belt drive transmissionembodiment for implementing one or more stages of a transmission.

Advantages of a belt or chain drive approach over the ballscrewapproaches described above include the ability to provide a fullyenclosable/sealable (without need for a bellows-type cover) powered legdevice. This facilitates component immersion in lubricating environment,and well as facilitating isolation from dirt, water, and other debris.As a result, this can extend the lifetime of transmission components.Another advantage of such a configuration is that it enables a greaterrange of motion of joint actuation, as opposed to a slider-crankmechanism (as used in a ballscrew configuration), which is generallylimited. Further, the belt or chain drive approach also allows thedevice to maintain a constant transmission ratio throughout range ofmotion, which is not generally possible in the slider-crank mechanismtypically used in a ballscrew configuration. Additionally, advantages ofa belt or chain drive approach is that it maintains constant mechanismgeometry throughout range of motion, belt and chain drive components aretypically less expensive than ballscrew components, and belt and chaindrive systems are typically characterized by lower audible noise thanballscrew configurations.

FIG. 27 shows an exemplary embodiment of a belt drive transmission 2700in accordance with an embodiment of the invention. As shown in FIG. 27,a stage of the transmission 2700 can be embodied as a belt drivetransmission, in which a belt 2702 is wrapped around the circumferenceof a larger diameter shaft, such as a first belt gear or pulley 2704,and also around the circumference of a smaller diameter shaft, such assecond belt gear or pulley 2706. In such embodiments, the belt 2702 canbe tensioned, using a tensioning device 2708. In one embodiment, thetensioning device 2708 can consist of a swing arm 2710, an additionalpulley 2712 attached to the end of swing arm 2710, and tensioning screw2714 for adjusting the swing arm 2710 to bias the additional pulley 2712against the belt 2702, such that friction between the belt 2702 and beltgears 2704 and 2706 enables the transmission of torque from betweensecond belt gear 2706 and first belt gear 2704. However, any other typeof tensioning device can be used in the various embodiments to tensionthe belt 2702. For example, in some embodiments, the tensioning device2708 can be a spring loaded device to automatically bias a pulley 2706or other object against belt 2702 to cause the necessary tension.

It is worth noting that although transmission 2700 is illustrated interms of a V-belt embodiment, the invention is not limited in thisregard and can be used with any type of belts. For example, the belt2702 can also be embodied as a flat belt, a round belt, a multi-groovebelt, a ribbed belt, and a toothed or cog belt, to name a few. Further,the belt gears 2704 and 2706 can be configured in accordance with thetype of belt being used.

In some embodiments, rather than utilizing a belt-based drive, achain-based drive can be provided. The configuration in such embodimentscan be substantially similar to that shown in FIG. 27. That is, a chaincan be provided in place of belt 2702 and gears 2704 and 2706 can beembodied as sprockets compatible with the chain. In such embodiments,the tensioning device 2708 described above can still be utilized tomaintain proper tension of the chain to enable the transmission oftorque from between sprockets in the transmission.

In some embodiments, instead of utilizing a tensioning device asdescribed above with FIG. 27, a pulley or sprocket can be configuredwith an eccentric mount. That is, configuring at least one of the drivegears in the transmission to allow an adjustment of its position. Thisis illustrated below with respect to FIGS. 28A-28D.

FIGS. 28A and 28B show side views of first and second positions,respectively, achievable for an exemplary embodiment of a chain drivetransmission 2800 including an eccentric mount in accordance with anembodiment of the invention. Similar to the transmission described abovewith respect to FIG. 27, transmission 2800 includes a first shaft 2802with first drive gears or sprockets 2804 and a second shaft 2806 withsecond drive gears or sprockets 2808 which can be coupled together viachains 2810 to transmit torques between sprockets 2804 and sprockets2808. Although FIGS. 28A and 28B show that the transmission of torquebetween sprockets 2804 and sprockets 2808 is performed using two sets ofsprockets (and thus using two chains), the embodiments are not limitedin this regard. Rather, any number of chains can be used in the variousembodiments.

As shown in FIGS. 28A and 28B, the first shaft 2802 is shown asincluding an additional sprocket 2812 for driving first shaft 2802. Sucha configuration can be used when multiple drive stages are provided.However, the various embodiments are not limited in this regard.

In transmission 2800, the first shaft 2802 is configured to beeccentric. That is, the position of the first shaft 2802 is adjustablerelative to the position of the second shaft 2806 so as to adjust thelateral separation between the shafts (i.e., to provide d_(A)≠d_(B)).Accordingly, this also provides a means to adjust the tension in a chain(or a belt) between the first shaft 2802 and the second shaft 2806. Toprovide the eccentric mount, the first shaft 2802 can be mounted in aleg device to an adjustable bearing mount 2814. The operation andconfiguration of an exemplary embodiment of the adjustable bearing mount2814 is illustrated with respect to FIG. 29.

FIG. 29 illustrates schematically the components for the adjustablebearing mount 2812. As shown in FIG. 29, the adjustable bearing mount2814 can include a top plate 2902 to which first shaft 2802 is attached,a bottom plate 2904, bearings 2906 between the top plate 2902 and thebottom plate 2904, and fasteners 2908. These components of theadjustable bearing mount 2814 can be disposed within an enclosure 2910.

In FIG. 29, the fasteners 2908 are shown as screws or bolts. However,the various embodiments are not limited to any particular bearing typeor design of screws or bolts and other bearing types or designs can beused without limitation. Further, the various embodiments are notlimited to screws or bolts and any other type of removable fastener canbe used without limitation. Additionally, FIG. 29 shows bearings 2906 asa collection of ball bearings disposed between plates 2902 and 2904.However, the various embodiments are not limited to any particularbearing type or design and other bearing types or designs can be usedwithout limitation.

In operation, the enclosure 2910 can be configured such that whenfasteners 2908 are loosened or removed, the bearings allow the top plate2902 can be repositioned relative to the bottom plate 2904 via bearings2906. Thus, when fasteners 2908 are replaced and tightened, the plates2902 and 2904 are biased against bearings 2906 to prevent further motionof the top plate 2902 relative to the bottom plate 2904.

Such a configuration allows adjustment of the position of first shaft2802. For example, this can allow the first shaft 2802 to transitionbetween a first position, as shown in FIG. 28A, in which a chain or belt2810 with reduced tension is provided, due to a reduced distance (d_(A))between first shaft 2802 and second shaft 2806, to a second position, asshown in FIG. 28B, in which a chain or belt 2814 with increased tensionis provided, due to an increased distance (d_(B)) between first shaft2802 and second shaft 2806. However, the various embodiments are notlimited to solely first and second positions. Rather, in the variousembodiments, the adjustable bear mount 2812 can be configured to allow avariety of positions for the first shaft 2806 relative to the secondshaft 2806.

A exemplary configuration of a powered leg prosthesis 3000 in accordancewith the discussion above is illustrated schematically in FIG. 30. Asshown in FIG. 30, the powered leg prosthesis 3000 includes a shank 3002with a powered knee joint 3004 and a powered ankle joint 3006. Thepowered knee joint 3004 includes a socket interface 3008 for attaching asocket 3010 or other device for attachment of the powered leg prosthesis3000 to an amputee. The powered ankle joint 3006 can have a foot portion3012 attached thereto.

The shank 3002 can consist of a single, discrete unit. However, in someembodiments, the shank can include an upper portion 3014 and a lowerportion 3016. Such a configuration allows the insertion of at least oneextension unit 3018 to allow the length of the shank 3002 to becustomized for the amputee.

Within each of the upper portion 3014 and the lower portion 3016, a beltor chain drive system can be implemented, as described above withrespect to FIGS. 27-29. For example, as shown in FIG. 30, the upperportion 3014 can include a first motor 3022, a first upper drive stage3024, and a second upper drive stage 3026 for providing power at thepowered knee joint 3004. Similarly, the lower portion 3016 can include asecond motor 3028, a first upper drive stage 3030, and a second upperdrive stage 3032 for providing power at the powered ankle joint 3006.Each stage can consist of the belt or chain drive stage. Additionally,each stage can be configured to include an eccentric mount, such asmounts 3034 and 3036, to adjust tension in the upper portion 3014 andlower portion 3016 respectively.

In addition to the components described above, the powered prostheticleg 3000 can include other components not illustrated in FIG. 30 forpurposes of clarity. For example, the powered prosthetic leg can includea control system or device, as previously described, and one or moresensors throughout the powered prosthetic leg, also as previouslydescribed. Thus control of the powered prosthetic leg 3000 can occurinsubstantially the same manner as described above.

Applicants present certain theoretical aspects above that are believedto be accurate that appear to explain observations made regardingembodiments of the invention. However, embodiments of the invention maybe practiced without the theoretical aspects presented. Moreover, thetheoretical aspects are presented with the understanding that Applicantsdo not seek to be bound by the theory presented.

While various embodiments of the invention have been described above, itshould be understood that they have been presented by way of exampleonly, and not limitation. Numerous changes to the disclosed embodimentscan be made in accordance with the disclosure herein without departingfrom the spirit or scope of the invention. Thus, the breadth and scopeof the invention should not be limited by any of the above describedembodiments. Rather, the scope of the invention should be defined inaccordance with the following claims and their equivalents.

Although the invention has been illustrated and described with respectto one or more implementations, equivalent alterations and modificationswill occur to others skilled in the art upon the reading andunderstanding of this specification and the annexed drawings. Inaddition, while a particular feature of the invention may have beendisclosed with respect to only one of several implementations, suchfeature may be combined with one or more other features of the otherimplementations as may be desired and advantageous for any given orparticular application.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. Furthermore, to the extent that the terms “including”,“includes”, “having”, “has”, “with”, or variants thereof are used ineither the detailed description and/or the claims, such terms areintended to be inclusive in a manner similar to the term “comprising.”

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this invention belongs. It isfurther understood that terms, such as those defined in commonly useddictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andwill not be interpreted in an idealized or overly formal sense unlessexpressly so defined herein.

1-22. (canceled)
 23. A control system for a powered joint in a legprosthesis having at least one of a powered ankle joint or a poweredknee joint, the system comprising: a processor; and a memory havingstored therein a plurality of code sections executable by the processor,the plurality of code comprising instructions for: receiving real-timeinformation from one or more sensors associated with the leg prosthesis,identifying one of a plurality of activity modes for the leg prosthesisbased on the real-time information to yield an instantaneous mode,selecting an active intra-modal controller for the leg prosthesis basedon the instantaneous mode, and generating control signals forcontrolling the powered joint using the active intra-model controllerand based on the real-time information.
 24. The control system of claim23, wherein the identifying comprises: extracting one or more featuresin real-time from one or more sensor signals; computing at least oneprobability value for each of the one or more features being associatedwith each of the plurality of activity modes; and selecting as theinstantaneous mode a one of the plurality activity modes for which theprobability values meet a criteria.
 25. The control system of claim 24,wherein the computing comprises: performing a principal componentanalysis of one or more features to obtain corresponding one or morereduced dimension feature vectors, and calculating the probabilityvalues based on the one or more reduced dimension feature vectors. 26.The control system of claim 23, wherein the computing comprisescalculating the probability values for each of the plurality of activitymodes using corresponding probably density functions dependent on valuesrepresented by the one or more features.
 27. The control system of claim26, wherein the corresponding probably density functions each compriseGaussian mixture models.
 28. The control system of claim 23, wherein thereal-time information comprises a plurality of samples over a period oftime, wherein the identifying is performed for each of the plurality ofsamples, and wherein the selecting comprises switching to an intra-modalcontroller for which a number of the plurality of samples correspond toa same instantaneous mode exceeds a threshold.
 29. The control system ofclaim 23, further comprising attenuating the control signals when theactive intra-modal controller is changed.
 30. A method for controlling apowered joint in a leg prosthesis having at least one of a powered anklejoint or a powered knee joint, the method comprising: receivingreal-time information from one or more sensors associated with the legprosthesis, identifying one of a plurality of activity modes for the legprosthesis based on the real-time information to yield an instantaneousmode, selecting an active intra-modal controller for the leg prosthesisbased on the instantaneous mode, and generating control signals forcontrolling the powered joint using the active intra-model controllerand based on the real-time information.
 31. The method of claim 30,wherein the identifying comprises: extracting one or more features inreal-time from one or more sensor signals; computing at least oneprobability value for each of the one or more features being associatedwith each of the plurality of activity modes; and selecting as theinstantaneous mode a one of the plurality activity modes for which theprobability values meet a criteria.
 32. The method of claim 31, whereinthe computing comprises: performing a principal component analysis ofone or more features to obtain corresponding one or more reduceddimension feature vectors, and calculating the probability values basedon the one or more reduced dimension feature vectors.
 33. The method ofclaim 30, wherein the computing comprises calculating the probabilityvalues for each of the plurality of activity modes using correspondingprobably density functions dependent on values represented by the one ormore features.
 34. The method of claim 33, wherein the correspondingprobably density functions each comprise Gaussian mixture models. 35.The control system of claim 30, wherein the real-time informationcomprises a plurality of samples over a period of time, wherein theidentifying is performed for each of the plurality of samples, andwherein the selecting comprises switching to an intra-modal controllerfor which a number of the plurality of samples correspond to a sameinstantaneous mode exceeds a threshold.
 36. The method of claim 30,further comprising attenuating the control signals when the activeintra-modal controller is changed.
 37. A computer-readable medium havingstored thereon a computer program executable by a computing devicecontrolling a powered joint in a leg prosthesis having at least one of apowered ankle joint or a powered knee joint, the computer programcomprising a plurality of code sections for causing the computing deviceto perform steps comprising: receiving real-time information from one ormore sensors associated with the leg prosthesis; identifying one of aplurality of activity modes for the leg prosthesis based on thereal-time information to yield an instantaneous mode; selecting anactive intra-modal controller for the leg prosthesis based on theinstantaneous mode; and generating control signals for controlling thepowered joint using the active intra-model controller and based on thereal-time information.
 38. The computer-readable medium of claim 37,wherein the identifying comprises: extracting one or more features inreal-time from one or more sensor signals; computing at least oneprobability value for each of the one or more features being associatedwith each of the plurality of activity modes; and selecting as theinstantaneous mode a one of the plurality activity modes for which theprobability values meet a criteria.
 39. The computer-readable medium ofclaim 38, wherein the computing comprises: performing a principalcomponent analysis of one or more features to obtain corresponding oneor more reduced dimension feature vectors, and calculating theprobability values based on the one or more reduced dimension featurevectors.
 40. The computer-readable medium of claim 37, wherein thecomputing comprises calculating the probability values for each of theplurality of activity modes using corresponding probably densityfunctions dependent on values represented by the one or more features.41. The computer-readable medium of claim 40, wherein the correspondingprobably density functions each comprise Gaussian mixture models. 42.The computer-readable medium of claim 37, wherein the real-timeinformation comprises a plurality of samples over a period of time,wherein the identifying is performed for each of the plurality ofsamples, and wherein the selecting comprises switching to an intra-modalcontroller for which a number of the plurality of samples correspond toa same instantaneous mode exceeds a threshold.
 43. The computer-readablemedium of claim 37, the computer program further comprising additionalcode sections for causing the computing device to perform the step ofattenuating the control signals when the active intra-modal controlleris changed.